The Senior Analytics Engineer plays a vital role in building data integration and warehousing solutions that support the organization's success. They prepare enterprise data for analysis to inform business strategies, combining the skills of data analysts and engineers with a focus on creating data models and communicating insights.

Sr Analytics Engineer collaborate with data teams to develop datasets and tools that empower end-users to interpret and assess data. They have diverse responsibilities including designing data models, gathering information, writing code, maintaining data documentation, communicating results, and maintaining data warehouse and analytics environments.

Responsibilities

Collaborate with cross-functional teams to plan, design, develop, implement, manage, and maintain data integration and warehousing solutions that support business goals. This includes translating business requirements into technical specifications, developing and maintaining solution documentation and training materials, and providing ongoing user support.
Ensure the ongoing operation of enterprise data systems related to data transfer, including designing, developing, testing, and maintaining data systems and components. Monitor and troubleshoot these systems to ensure service continuity and participate in capacity planning and architecture design.
Serve as a subject matter expert for data principles and stay current with new data warehouse and BI technologies. Contribute to developing and documenting technical standards and best practices for the organization.
Collaborate with cross-functional teams to design, build, test, deploy, and support solutions that meet business needs.
Help drive improvements to the features, reliability, performance, and efficiency of Enterprise Data and Analytics platforms.
Assist technical leadership in designing and implementing the company-wide data architecture strategy.
Collaborate with engineering teams to identify and resolve pain points and promote best practices.
Partner with various teams to transform concepts into requirements and requirements into services and tools.
Engineer efficient, adaptable, and scalable architecture for all stages of the data lifecycle (ingest, streaming, structured and unstructured storage, search, aggregation) to support a variety of data applications.
Create and maintain systems that load and transform large data sets from various internal sources.
Serve as a subject matter expert for data-related technologies.
Design and maintain data models for new and existing production systems and maintain data schema versioning.
Develop and support backend components for data-centric integrations and repositories for analytical reporting.
Work with Data Analysts and Business Intelligence team members to create data-driven insights and reports for senior management and operations leadership.
Perform daily monitoring, administration, repair, and maintenance of data technologies and related technologies in all environments.
Assist with managing the information flow for the organization, including the integrity, efficiency, and availability of data.
Develop and implement data standards, ensure metadata is captured correctly, and create methods for monitoring and reporting data incidents.
Create and maintain common data dictionaries and tools/methods that support data standards for the organization.
Analyze and oversee strategies to enhance data reliability and minimize redundancies.
Work with IT personnel to develop data quality standards.
Assist with data monitoring and provide guidance to management on streamlining data management.
May assist with creating key performance indicators and provide performance results to colleagues and management.

Qualifications

Bachelor's degree in computer science or related field, or equivalent experience.
Experience with design, administration, and/or data-dependent production systems.
Experience designing and supporting ETL/ELT solutions for reporting, dashboards, and analytics.
Strong documentation, data manipulation, and coding skills.
Proven ability to learn independently and troubleshoot effectively.
Ability to investigate complex business problems, develop and present solutions.
Excellent communication, interpersonal, analytical, and problem-solving skills.
Demonstrated ability to work effectively in both team and individual settings.
Experience using APIs for data transfer between systems and platforms.
Effective time management and prioritization skills.
Continuous improvement mindset and solid understanding of SDLC

Preferred Experience

Data visualization, reporting and dashboard development (Tableau, PowerBI, etc.).
Programming (T-SQL, PowerShell, Python, etc.).
DevOps and Agile Development processes.

Pay Transparency
TierPoint is committed to practices that promote pay equity and transparency. We provide a compensation range for roles that may be hired in locations with pay transparency law requirements. It’s important to note the pay range may be narrower than displayed, as various factors are used to determine the offered compensation package including skill set, level of experience, geographic locations, and other relevant factors- i.e. budgetary requirements.

$120,653.86 - $180,980.79

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